Digital images can be captured with a three-hundred and sixty degree field of view (360° FOV) camera and then stitched together to form a combined 360-degree field of view image by image processing techniques that combine the captured digital images. A 360-degree FOV camera can be two cameras in a back-to-back configuration, with each camera having a one-hundred and eighty degree (180°) field of view to capture approximately half of the overall 360-degree field of view image. When the two captured images from the two cameras are stitched together to form the 360-degree field of view image, there can be a noticeable seam between where the images are joined, such as caused by differences in the color and/or intensity response of the two cameras, by non-exact lens shading correction between the two cameras, or by image flare from direct or reflected lighting that affects one of the captured images and not the other. This noticeable seam between the two captured images in the combined 360-degree field of view image is an objectionable and unwanted artifact in the combined image.
Conventional image processing solutions to remove the appearance of a seam between captured images are overly complicated and processing intensive solutions, and tend to introduce blurring and unwanted image artifacts in the resulting image. For example, an averaging technique and an alpha-blending technique introduce blurring in the resulting image along the seam, and can introduce unwanted image artifacts in the resulting image. Other processing intensive solutions include Poisson blending, solving Poisson equations to blend the images, and a pyramid blending solution that creates image pyramids, using Gaussian or Laplacian transforms to blend the images using masked pyramid weights. Notably, these blending solutions are ineffective for images that have color and intensity differences along a seam at their boundaries, and can also introduce the blurring and unwanted image artifacts in the resulting image.